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Creole languages originate as a pidgin language. Pidgins typically develop in a colony situation or any time there is a power differential between two groups in one location that do not share a language. A pidgin develops as a necessary method of communication between a local population and a more powerful colonizer or invader. A pidgin is not spoken natively because it is developed after the age of acquisition in humans (12-14), it is therefore a fabricated amalgam. A creole is a full fledged language that develops in the location that a pidgin has been spoken for a significant period of time, basically enough time for children to have grown up with the pidgin and had time to combine it into a new native language, the creole.

It's definitely not a new technique. It's purpose in bioinformatics is sequence comparisons. It calculates the mean and standard deviation of a fixed size piece of the sequence. It lends itself very well toward malware analysis.

There may be cases where a single "species" of bacteria has a varying rate of horizontal transfer based on its host species. It may have more exposure to a different species of bacteria that it is able to trade genes with because that other species is exclusive to one of the two hosts rather than both. In cases like these, you could name each by its code. I think the ultimate goal is to make clear naming distinctions that reflect actual differences in populations of organisms.

I think you''re mostly correct, except for the case of organisms with horizontal gene transfer such as bacteria and archaea. The current naming convention breaks down when it is applied to this type of organism.

Last month, at ShmooCon a talk was given about spatial analysis of malware samples. The technique is borrowed directly from bioinformatics. This is a great example of techniques from Biology being used effectively in the IT security realm.

I hope that the researcher involved in naming organisms based on hash algorithms chooses context triggered piecewise hashes (CTPH) AKA fuzzy hashing or a similarity hash algorithm rather than an algorithm like SHA512. Google's simhash or at least the ideas of this type of algorithm would lend itself much better to the naming of organisms.

FYI: a FOSS implementation of fussy hashing is called ssdeep. The project site is here. This is an implementation that is widely used in open source malware analysis tools like Cuckoo Sandbox.

Data expands to fill the space available. It doesn't matter what the super fast super large digital thing is this year, at some point it will feel slow and old. Remember 10Mbit ethernet? That was TEN times as fast as 1Mbit!!!!!! It GIFs loaded instantly from your fileserver compared to waiting for them to load on dialup.

I'm curious as to whether or not SeaBIOS can be integrated into VirtualBox rather than using the watcom bios. This is the BIOS that is utilized by KVM/QEMU and therefore most OpenStack implementation that I've used have SeaBIOS.